I'm new to Weka (and machine learning) so this question would be a bit silly.
So I have 2 models built using J48 and RandomForest (both run with 10-fold cross-validation mode) on a 40,000-tuple training set. I also have 6 different smaller test sets, each has around 8000 tuples.
Now I want to compare how these 2 classification algorithms perform after testing their models (I have the predictions reported).
The problem is, I don't have a good understanding of the reported predictions so I don't know how to compare the prediction of each to see which one is better in terms of accuracy.